Databricks reaches $188B valuation in latest funding round

Databricks announced Thursday that it has secured funding at a $188 billion valuation, led by Coatue, marking the latest milestone in an aggressive fundraising campaign that has seen the company more than triple its valuation in 18 months.

The company did not disclose the exact amount raised, stating only that the round has not yet closed and is expected to finalize later this summer. Other outlets have reported the raise at approximately $3 billion, according to TechCrunch, which first reported the details.

Rapid-fire fundraising streak

This marks Databricks' fourth major funding round since December 2024. The company raised $10 billion at a $62 billion valuation in December 2024, followed by $1 billion at $100 billion in September 2025, and $5 billion at $134 billion just five months ago in February 2026.

The frequency of raises has sparked commentary on social media, with observers joking about running out of alphabet letters for series designations. One person posted they were "turning on alerts for when we get a Series AA."

Why it matters

Databricks represents a textbook case of successful corporate repositioning in the AI era. Founded in 2013 as a big data analytics platform, the company has leveraged its existing position managing enterprise data to become a key AI infrastructure provider. This transition has unlocked unprecedented access to capital at valuations that would have been unthinkable for a traditional data analytics company. The company's ability to raise at escalating valuations also reflects investor appetite for established enterprise software companies with AI capabilities, rather than just pure-play AI startups.

From big data to AI infrastructure

Databricks initially built its business on enabling enterprises to store massive amounts of data in the cloud while maintaining fast analytics capabilities. When enterprise AI adoption accelerated, the company was well-positioned to pivot, already sitting on the data infrastructure companies needed.

The company has since launched multiple AI-focused products, including Lakebase, a database designed for AI agents; Unity, an AI gateway; and Omnigent, a management layer for multiple agents.

Champion of open-weight models

Databricks has emerged as a prominent advocate for cost-effective open-weight models, particularly Chinese-based options like Z.ai's GLM 5.2 for coding tasks. Last week, CEO Ali Ghodsi published internal benchmarking results comparing AI models on tasks performed by the company's 3,000 software engineers.

The analysis found that "open models, and GLM 5.2 in particular, are now able to handle even the highest level of task difficulty" in coding at lower total cost than proprietary models from Anthropic and OpenAI.

The research also revealed that the choice of agentic coding harness—the tool that wraps around a model to manage context and instructions—significantly impacts costs. The company found that open-source harness Pi excelled at managing context, delivering quality results at lower cost.

"The lesson here isn't that one harness is always cheaper or that native harnesses are worse. Instead, model choice is only one piece of the puzzle," the company stated.

TechCrunch first reported the funding announcement and valuation details.